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Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in simulating physical and mathematical systems. Because of their reliance on repeated computation of random or pseudo-random numbers, these methods are most suited to calculation by a computer and tend to be used when it is unfeasible or impossible to compute an exact result with a deterministic algorithm.
Learn more about quantum dots from the many resources on this site, listed below. More information on Monte Carlo method can be found here.
Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing
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13 Feb 2008 | | Contributor(s):: Jeffrey C Grossman, Elif Ertekin
In this lecture, we discuss various methods for finding the ground state structure of a given system by minimizing its energy. Derivative and non-derivative methods are discussed, as well as the importance of the starting guess and how to find or generate good initial structures. We also briefly...
Homework for Monte Carlo Method: High field transport in Bulk Si
06 Jan 2006 | | Contributor(s):: Muhammad A. Alam
This homework assignment is part of ECE 656 "Electronic Transport in Semiconductors" (Purdue University). It contains 10 problems which lead students through the simulation of high-field transport in bulk silicon.